A Scaleless Data Model for Direct and Progressive Spatial Query Processing

Sai Sun, Sham Prasher, Xiaofang Zhou

Research output: Chapter in Book/Conference Proceeding/ReportBook Chapterpeer-review

Abstract

A progressive spatial query retrieves spatial data based on previous queries (e.g., to fetch data in a more restricted area with higher resolution). A direct query, on the other side, is defined as an isolated window query. A multi-resolution spatial database system should support both progressive queries and traditional direct queries. It is conceptually challenging to support both types of query at the same time, as direct queries favour location-based data clustering, whereas progressive queries require fragmented data clustered by resolutions. Two new scaleless data structures are proposed in this paper. Experimental results using both synthetic and real world datasets demonstrate that the query processing time based on the new multiresolution approaches is comparable and often better than multi-representation data structures for both types of queries.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
EditorsShan Wang, Katsumi Tanaka, Shuigeng Zhou, Tok Wang Ling, Jihong Guan, Dongqing Yang, Fabio Grandi, Eleni Mangina, Il-Yeol Song, Heinrich C. Mayr
PublisherSpringer Verlag
Pages148-159
Number of pages12
ISBN (Print)3540237224, 9783540237228
DOIs
Publication statusPublished - 2004
Externally publishedYes

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3289
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

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